Description and Composition of Bio-Inspired Design Patterns:

The Gradient Case

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Jose Luis Fernandez-Marquez University of Geneva, Switzerland Joseluis.fernandez@unige.ch http://iss.unige.ch

In collaboration with: Giovanna Di Marzo Serugendo – University of Geneva, Switzerland Josep Lluis Arcos – IIIA-CSIC, Barcelona, Spain Mirko Viroli - University of Bologna, Italy Sara Montagna - University of Bologna, Italy

Outline

  Motivation   Goal   Bio-Inspired Design Patterns

  Gradient Pattern   Chemotaxis Pattern

  Applications   Framework: SAPERE Project   Conclusions and Future research

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Motivation

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  Characterized by:

  Large Scale

  Openness

  Unpredictability

  Wide range of new applications

  Requirements:

  Scalability

  Robustness

Traditional Approaches (centralised, not distributed)

Motivation

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  Bio-Inspired Self-Organising mechanisms have been applied in those infrastructures, achieving results that go beyond traditional approaches, (ACO, PSO, flocking, Digital pheromones….) . However,

  The knowledge and experience on how, when, and where to use them is spread across the corresponding literature.

  It is very difficult to grasp what are their capabilities and weakness.

Goal

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  To analyse existing literature, providing a catalogue of Bio-inspired Mechanisms for Self-Organizing Systems.

  To describe those mechanisms as design patterns, identifying how, where, and when to be applied.

  Identify the relationship between the presented mechanisms, providing a better description and making it easier to compose new patterns or adapt the existing patterns to solve new problems.

  Demonstrate the applicability of those mechanisms tackling with different domains:

  Dynamic Optimization

  Spatial Computing

  Sensor Networks

Bio-Inspired Design Pattern

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Bio-Inspired Design Pattern

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Bio-Inspired Design Patterns

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Repulsion Evaporation Replication Aggregation Spreading

Flocking Foraging Chemotaxis Morphogenesis Quorum Sensing

Digital Pheromones Gradients Gossip

Bio-Inspired Design Patterns

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How When Where

Aliases Biological Inspiration Related Patterns

Typical Case

Known Uses Problem Environment

Solution

Forces

Entities / Dynamics

Implementation

Consequences

Pattern Description

The Gradient Pattern

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  Problem: Large systems suffer from lack of global knowledge to estimate the consequences of the actions performed by other agents beyond their communication range.

  Solution: Information spreads from the location it is initially deposited and aggregates when it meets other information. During spreading, additional information about the sender's distance and direction is provided: either through a distance value (incremented or decremented); or by modifying the information to represent its concentration (lower concentration when information is further away).

  Abstract transition rule:

The Gradient Pattern

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  Dynamics:

The Gradient Pattern

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  Dynamics:

The Chemotaxis Pattern

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  Problem: Decentralised motion coordination aiming at detecting sources or boundaries of events.

  Solution: Agents locally sense gradient information and follow the gradient in a specified direction (either follow higher gradient values, lower gradient values, or equipotential lines of gradients).

  Abstract transition rule:

The Chemotaxis Pattern

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  Dynamics:

Applications

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  Dynamic Optimisation:   We extended PSO with the Evaporation Pattern to deal with

dynamic and noisy optimisation.   Hovering Information in Spatial Computing:

  We defined and analysed a collection of algorithms based on the Replication Pattern and the Repulsion Pattern, for persistent storage of information at specific geographical areas.

  Detecting Diffuse Events Sources   We implemented the Chemotaxis Pattern for localizing

dynamically changing diffuse events using WSN.

FACULTÉ DES SCIENCES ÉCONOMIQUES ET SOCIALES Département des Hautes Etudes Commerciales -HEC

Framework: SAPERE project

  Theoretical and practical framework for decentralized development and execution of self-aware and adaptive services for future and emerging pervasive network scenarios.   Chemical Interactions among Services

  Smooth data/service distinction   Spontaneous interactions of

available services   Bio-chemical reactions

  Middleware for Android phones / tablets   Context-awareness (user, situation recognition)   Case Study

  Focus on public/private displays for crowd steering   Domains

  Context-Aware Advertisement, Crowd Steering, User guidance   EU Funded Project (SAPERE: http://www.sapere-project.eu)

  Collaboration: U Geneva, U Bologna, U Modena, U Linz, U St-Andrews   2010-2013

FACULTÉ DES SCIENCES ÉCONOMIQUES ET SOCIALES Département des Hautes Etudes Commerciales -HEC

Framework: SAPERE project

Crowd Steering through Self-Organising Public Displays

•  Collaborative displays

•  Self-organising spontaneous interactions   Bio-inspired (gradients, gossip,

stigmergy, flocking)

Conclusions

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  This work is a step forward for engineering self-Organising Systems.

  We presented a catalogue of bio-inspired Self-Organising mechanisms, as design patterns.

  We analysed the relations between the mechanisms, making easier their composition and adaptation to solve new problems.

  We contributed in different domains using bio-inspired Self-Organising Mechanisms:

  Dynamic Optimisation (Evaporation mechanism)   Sensor Networks (Chemotaxis mechanism)   Spatial Computing (Replication + repulsion)

Future Works

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  SAPERE Project:   Add New Patterns in the catalogue.   Self-Adaptation of parameters.   Self-Composition of patterns.   Implementation of services.

Any questions?

Thank you for your attention!

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Jose Luis Fernandez-Marquez

Joseluis.fernandez@unige.ch